Recent years have shown a proliferation in the number of individuals who operate computing devices (e.g., smartphones, tablets, laptops, etc.). Typically, users migrate to various locations throughout the day, and, as a result, clusters of computing devices tend to continually form and disintegrate. A cluster can include, for example, two or more computing devices that share a common user account, two or more computing devices that share similar hardware features, and the like. In general, a cluster can form when at least two computing devices are communicatively coupled to one another via a Personal Area Network (PAN) (e.g., via a Bluetooth® connection, a direct WiFi connection, a Near Field Communication (NFC) connection, etc.). These local networks are typically formed when the computing devices transmit (i) identifying information that enables the computing devices to establish a particular level of trust, and (ii) connection information, which together enable the computing devices to form a communicative coupling. In turn, the computing devices can implement useful functionality, e.g., performing direct file swaps between one another.
Despite the foregoing connectivity techniques, computing devices continue to work in isolation when carrying out various tasks that are involved with providing internet-category connectivity (e.g., push notifications, Voice over Internet Protocol (VoIP) phone calls, geolocation updates, and the like). Notably, a considerable amount of energy is consumed when carrying out these tasks, as application processors and radios within the computing devices need to continually wake in order to transmit, receive, and process data. This is unfortunate considering that, in many cases, there exists an overlap between data that is processed by two or more computing devices within a cluster, yet the computing devices continue to process the overlapped data in an isolated and redundant manner.